| Title |
Decomposition Analysis of Energy Use for Water Supply: From the Water-Energy Nexus Perspective |
| Authors |
유재호 ( Yoo Jae-ho ) ; 조연희 ( Jo Yeon Hee ) ; 김하나 ( Kim Hana ) ; 전의찬 ( Jeon Eui Chan ) |
| DOI |
https://doi.org/10.15681/KSWE.2022.38.5.240 |
| Keywords |
Decomposition analysis; LMDI; Water-energy nexus; Water-related energy use |
| Abstract |
Water and energy are inextricably linked and referred to as ‘Water-Energy Nexus’. Recently, this topic has been drawing a lot of attention from various studies due to the exacerbated water availability. Korea’s water and energy consumption has been increasing consistently, which calls for better management. This paper aims to identify changes in electricity consumption in relation to water intake and purification processes. Using Log Mean Divisia Index (LMDI) Decomposition Analysis method, this study attributes the changes to major factors such as; Total population (population effect), household/population (structure effect), GDP/household (economic effect), and water-related energy use/GDP (unit effect). The population effect, structure effect, and economic effect contributed to an increase in water-related electricity consumption, while the unit effect contributed to a decrease. As of 2019, the economic effect increased the water supply sector’s electricity consumption by 534 GWh, the population effect increased by 73 GWh, and the structure effect increased by 243 GWh. In contrast, the unit effect decreased the electricity consumption by -461 GWh. We would like to make the following suggestions based on the findings of this study; first, the unit effect must be improved by increasing the energy efficiency of water intake and purification plants and installing renewable energy power generation facilities. Second, the structure effect is expected to increase over time, and to mitigate it, water consumption must be reduced through water conservation policies and the improvement of water facilities. Finally, the findings of this study are expected to be used as foundational data for integrated water and energy management. |